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Efficient Deduplication on Cloud Environment Using Bloom Filter and IND-CCA2 Secured Cramer Shoup Cryptosystem

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Intelligent Data Communication Technologies and Internet of Things (ICICI 2019)

Abstract

Cloud Service Providers (CSP) offers several services over the internet to the cloud users. One of the predominant services offered to the cloud users is data storage. With the rapid growth of digital data, redundancy has become the bottleneck issue in cloud computing environment. Storing identical copies of user data increases the storage overhead. The traditional way of performing deduplication is by comparing the cipher texts, which will result in high time complexity and heavy load on users. To utilize the cloud storage effectively and to reduce the work load of cloud users, a novel inline data deduplication method is created based on Bloom filter. The proposed scheme combines the application of bloom filter and Cramer Shoup cryptosystem to perform secure inline deduplication. Two matrices are created such as keyword matrix and file matrix based on the application of the bloom filter to perform deduplication on the cloud storage. The empirical study of the proposed deduplication technique is carried out on the Eucalyptus v4.2.0 open source private cloud on top of the Xeon processor with 64 GB of RAM Speed. It has been observed that the proposed deduplication improves the efficiency and effectiveness of the deduplication compared to the traditional deduplication algorithms.

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Acknowledgement

The work of this paper is financially sponsored by Science and Engineering Research Board (SERB), Department of Science and Technology (DST), Government of India. The Grant Number is ECR/2016/000546.

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Correspondence to Y. Mohamed Sirajudeen .

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Mohamed Sirajudeen, Y., Muralidharan, C., Anitha, R. (2020). Efficient Deduplication on Cloud Environment Using Bloom Filter and IND-CCA2 Secured Cramer Shoup Cryptosystem. In: Hemanth, D., Shakya, S., Baig, Z. (eds) Intelligent Data Communication Technologies and Internet of Things. ICICI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-030-34080-3_80

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